With increasing availability of 3 Dimensional (3D) data acquisition devices such as Kinect™, researchers are inclining towards exploiting 3D information for a variety of applications such as change detection in a scene, industrial quality control, pose tracking, and the like. Registration of 3D point clouds is a critical initial step for many associated processes. Generally, two point clouds, referred to as reference point cloud and template point cloud respectively of an object or scene are captured at two time instances, possibly from different camera positions. The scene may have undergone some changes during this time interval. Registration refers to the process of translating, rotating and scaling the template such that it optimally aligns with the reference. Noise, outliers and missing parts are challenges to be addressed during registration.